Overview

Dataset statistics

Number of variables12
Number of observations136
Missing cells2
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.1 KiB
Average record size in memory99.0 B

Variable types

Numeric2
Categorical5
Text3
DateTime2

Dataset

Description보령시 개발행위허가정보(개발행위허가에 대한 위치, 지목, 지역, 면적, 개발행위명, 허가목적, 허가일 등을 제공합니다.)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=416&beforeMenuCd=DOM_000000201001001000&publicdatapk=15039678

Alerts

시군 has constant value ""Constant
데이터기준일 has constant value ""Constant
리 has a high cardinality: 51 distinct valuesHigh cardinality
읍면동 is highly overall correlated with 리High correlation
리 is highly overall correlated with 읍면동High correlation
연번 has unique valuesUnique
번지 has unique valuesUnique

Reproduction

Analysis started2024-01-09 23:13:45.888641
Analysis finished2024-01-09 23:13:47.204553
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct136
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.5
Minimum1
Maximum136
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-01-10T08:13:47.272346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7.75
Q134.75
median68.5
Q3102.25
95-th percentile129.25
Maximum136
Range135
Interquartile range (IQR)67.5

Descriptive statistics

Standard deviation39.403892
Coefficient of variation (CV)0.57523929
Kurtosis-1.2
Mean68.5
Median Absolute Deviation (MAD)34
Skewness0
Sum9316
Variance1552.6667
MonotonicityStrictly increasing
2024-01-10T08:13:47.413345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
95 1
 
0.7%
89 1
 
0.7%
90 1
 
0.7%
91 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
96 1
 
0.7%
70 1
 
0.7%
Other values (126) 126
92.6%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%
131 1
0.7%
130 1
0.7%
129 1
0.7%
128 1
0.7%
127 1
0.7%

시군
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
보령시
136 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row보령시
2nd row보령시
3rd row보령시
4th row보령시
5th row보령시

Common Values

ValueCountFrequency (%)
보령시 136
100.0%

Length

2024-01-10T08:13:47.549052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T08:13:47.638391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보령시 136
100.0%

읍면동
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)13.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
천북
23 
남포
15 
청소
14 
주교
14 
웅천
13 
Other values (13)
57 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row내항
2nd row대천
3rd row주교
4th row죽정
5th row주산

Common Values

ValueCountFrequency (%)
천북 23
16.9%
남포 15
11.0%
청소 14
10.3%
주교 14
10.3%
웅천 13
9.6%
오천 9
 
6.6%
주산 7
 
5.1%
청라 6
 
4.4%
대천 6
 
4.4%
주포 5
 
3.7%
Other values (8) 24
17.6%

Length

2024-01-10T08:13:47.735447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
천북 23
16.9%
남포 15
11.0%
청소 14
10.3%
주교 14
10.3%
웅천 13
9.6%
오천 9
 
6.6%
주산 7
 
5.1%
청라 6
 
4.4%
대천 6
 
4.4%
동대 5
 
3.7%
Other values (8) 24
17.6%

리
Categorical

HIGH CARDINALITY  HIGH CORRELATION 

Distinct51
Distinct (%)37.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
27 
원산도
 
6
주교
 
6
낙동
 
5
양항
 
5
Other values (46)
87 

Length

Max length4
Median length2
Mean length2.4338235
Min length1

Unique

Unique23 ?
Unique (%)16.9%

Sample

1st row<NA>
2nd row<NA>
3rd row송학
4th row<NA>
5th row야룡

Common Values

ValueCountFrequency (%)
<NA> 27
19.9%
원산도 6
 
4.4%
주교 6
 
4.4%
낙동 5
 
3.7%
양항 5
 
3.7%
학성 5
 
3.7%
삼현 5
 
3.7%
하만 4
 
2.9%
관창 4
 
2.9%
죽림 4
 
2.9%
Other values (41) 65
47.8%

Length

2024-01-10T08:13:47.852596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 27
19.9%
주교 6
 
4.4%
원산도 6
 
4.4%
낙동 5
 
3.7%
양항 5
 
3.7%
학성 5
 
3.7%
삼현 5
 
3.7%
하만 4
 
2.9%
관창 4
 
2.9%
죽림 4
 
2.9%
Other values (41) 65
47.8%

번지
Text

UNIQUE 

Distinct136
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-01-10T08:13:48.104245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length6.4044118
Min length2

Characters and Unicode

Total characters871
Distinct characters20
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique136 ?
Unique (%)100.0%

Sample

1st row376
2nd row1203-6
3rd row244-2
4th row229
5th row452-4 외 1
ValueCountFrequency (%)
외 41
 
18.1%
1 23
 
10.1%
2 6
 
2.6%
3 4
 
1.8%
외1 3
 
1.3%
5 3
 
1.3%
177-3 2
 
0.9%
650-60 2
 
0.9%
591 2
 
0.9%
23일 2
 
0.9%
Other values (139) 139
61.2%
2024-01-10T08:13:48.499960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 144
16.5%
- 102
11.7%
92
10.6%
2 84
9.6%
3 59
6.8%
7 57
 
6.5%
5 53
 
6.1%
4 49
 
5.6%
외 46
 
5.3%
8 41
 
4.7%
Other values (10) 144
16.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 602
69.1%
Dash Punctuation 102
 
11.7%
Space Separator 92
 
10.6%
Other Letter 74
 
8.5%
Other Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 144
23.9%
2 84
14.0%
3 59
9.8%
7 57
 
9.5%
5 53
 
8.8%
4 49
 
8.1%
8 41
 
6.8%
9 41
 
6.8%
6 39
 
6.5%
0 35
 
5.8%
Other Letter
ValueCountFrequency (%)
외 46
62.2%
산 16
 
21.6%
월 4
 
5.4%
일 4
 
5.4%
지 2
 
2.7%
번 1
 
1.4%
필 1
 
1.4%
Dash Punctuation
ValueCountFrequency (%)
- 102
100.0%
Space Separator
ValueCountFrequency (%)
92
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 797
91.5%
Hangul 74
 
8.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 144
18.1%
- 102
12.8%
92
11.5%
2 84
10.5%
3 59
7.4%
7 57
 
7.2%
5 53
 
6.6%
4 49
 
6.1%
8 41
 
5.1%
9 41
 
5.1%
Other values (3) 75
9.4%
Hangul
ValueCountFrequency (%)
외 46
62.2%
산 16
 
21.6%
월 4
 
5.4%
일 4
 
5.4%
지 2
 
2.7%
번 1
 
1.4%
필 1
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 797
91.5%
Hangul 74
 
8.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 144
18.1%
- 102
12.8%
92
11.5%
2 84
10.5%
3 59
7.4%
7 57
 
7.2%
5 53
 
6.6%
4 49
 
6.1%
8 41
 
5.1%
9 41
 
5.1%
Other values (3) 75
9.4%
Hangul
ValueCountFrequency (%)
외 46
62.2%
산 16
 
21.6%
월 4
 
5.4%
일 4
 
5.4%
지 2
 
2.7%
번 1
 
1.4%
필 1
 
1.4%

지목
Categorical

Distinct31
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
답
41 
임
20 
전
18 
장
17 
대
8 
Other values (26)
32 

Length

Max length9
Median length1
Mean length1.4264706
Min length1

Unique

Unique20 ?
Unique (%)14.7%

Sample

1st row답
2nd row주
3rd row임
4th row장
5th row전

Common Values

ValueCountFrequency (%)
답 41
30.1%
임 20
14.7%
전 18
13.2%
장 17
12.5%
대 8
 
5.9%
창 2
 
1.5%
임+전 2
 
1.5%
전+임 2
 
1.5%
전+대 2
 
1.5%
잡 2
 
1.5%
Other values (21) 22
16.2%

Length

2024-01-10T08:13:48.638762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
답 41
30.1%
임 20
14.7%
전 18
13.2%
장 17
12.5%
대 8
 
5.9%
전+대 2
 
1.5%
잡 2
 
1.5%
목 2
 
1.5%
전+임 2
 
1.5%
임+전 2
 
1.5%
Other values (21) 22
16.2%

지적(제곱미터)
Real number (ℝ)

Distinct134
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20272.382
Minimum18
Maximum655901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.3 KiB
2024-01-10T08:13:48.768725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile371.5
Q11434.75
median3568.5
Q36971.5
95-th percentile71797.75
Maximum655901
Range655883
Interquartile range (IQR)5536.75

Descriptive statistics

Standard deviation80324.129
Coefficient of variation (CV)3.9622442
Kurtosis50.707042
Mean20272.382
Median Absolute Deviation (MAD)2473.5
Skewness6.9169249
Sum2757044
Variance6.4519657 × 109
MonotonicityNot monotonic
2024-01-10T08:13:48.895934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
992 2
 
1.5%
2810 2
 
1.5%
377 1
 
0.7%
20878 1
 
0.7%
1645 1
 
0.7%
655901 1
 
0.7%
5106 1
 
0.7%
773 1
 
0.7%
5811 1
 
0.7%
18 1
 
0.7%
Other values (124) 124
91.2%
ValueCountFrequency (%)
18 1
0.7%
84 1
0.7%
126 1
0.7%
232 1
0.7%
289 1
0.7%
330 1
0.7%
355 1
0.7%
377 1
0.7%
389 1
0.7%
481 1
0.7%
ValueCountFrequency (%)
655901 1
0.7%
613590 1
0.7%
211450 1
0.7%
158260 1
0.7%
132425 1
0.7%
85472 1
0.7%
77242 1
0.7%
69983 1
0.7%
65052 1
0.7%
50648 1
0.7%

용도지역
Categorical

Distinct25
Distinct (%)18.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
계획관리
39 
농림(농업진흥)
20 
보전관리
16 
생산관리
14 
농림지역(농업진흥)
9 
Other values (20)
38 

Length

Max length16
Median length4
Mean length5.7132353
Min length2

Unique

Unique11 ?
Unique (%)8.1%

Sample

1st row자연녹지
2nd row준공업
3rd row보전관리
4th row계획관리
5th row생산관리

Common Values

ValueCountFrequency (%)
계획관리 39
28.7%
농림(농업진흥) 20
14.7%
보전관리 16
11.8%
생산관리 14
 
10.3%
농림지역(농업진흥) 9
 
6.6%
자연녹지 7
 
5.1%
준공업 4
 
2.9%
일반공업 4
 
2.9%
농림지역 2
 
1.5%
제2종일반주거 2
 
1.5%
Other values (15) 19
14.0%

Length

2024-01-10T08:13:49.029565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계획관리 43
29.9%
농림(농업진흥 20
13.9%
보전관리 17
 
11.8%
생산관리 14
 
9.7%
농림지역(농업진흥 9
 
6.2%
자연녹지 8
 
5.6%
준공업 4
 
2.8%
일반공업 4
 
2.8%
농림지역 3
 
2.1%
농림 2
 
1.4%
Other values (14) 20
13.9%

허가면적(제곱미터)
Text

Distinct122
Distinct (%)90.4%
Missing1
Missing (%)0.7%
Memory size1.2 KiB
2024-01-10T08:13:49.310230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.4
Min length2

Characters and Unicode

Total characters459
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)84.4%

Sample

1st row377
2nd row95
3rd row560
4th row416
5th row
ValueCountFrequency (%)
100 3
 
2.3%
99 3
 
2.3%
197 2
 
1.5%
455 2
 
1.5%
516 2
 
1.5%
50 2
 
1.5%
934 2
 
1.5%
18 1
 
0.8%
795 1
 
0.8%
1417 1
 
0.8%
Other values (111) 111
85.4%
2024-01-10T08:13:49.718365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 59
12.9%
5 51
11.1%
9 48
10.5%
4 46
10.0%
0 45
9.8%
2 44
9.6%
6 42
9.2%
8 39
8.5%
3 37
8.1%
7 33
7.2%
Other values (4) 15
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 444
96.7%
Space Separator 12
 
2.6%
Other Letter 3
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 59
13.3%
5 51
11.5%
9 48
10.8%
4 46
10.4%
0 45
10.1%
2 44
9.9%
6 42
9.5%
8 39
8.8%
3 37
8.3%
7 33
7.4%
Other Letter
ValueCountFrequency (%)
공 1
33.3%
작 1
33.3%
물 1
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 456
99.3%
Hangul 3
 
0.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 59
12.9%
5 51
11.2%
9 48
10.5%
4 46
10.1%
0 45
9.9%
2 44
9.6%
6 42
9.2%
8 39
8.6%
3 37
8.1%
7 33
7.2%
Hangul
ValueCountFrequency (%)
공 1
33.3%
작 1
33.3%
물 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 456
99.3%
Hangul 3
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 59
12.9%
5 51
11.2%
9 48
10.5%
4 46
10.1%
0 45
9.9%
2 44
9.6%
6 42
9.2%
8 39
8.6%
3 37
8.1%
7 33
7.2%
Hangul
ValueCountFrequency (%)
공 1
33.3%
작 1
33.3%
물 1
33.3%

허가일자
Date

Distinct104
Distinct (%)77.0%
Missing1
Missing (%)0.7%
Memory size1.2 KiB
Minimum2022-03-06 00:00:00
Maximum2023-12-01 00:00:00
2024-01-10T08:13:49.857113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:13:50.004929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

허가내용
Text

Distinct90
Distinct (%)66.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-01-10T08:13:50.248989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length14.933824
Min length4

Characters and Unicode

Total characters2031
Distinct characters163
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique73 ?
Unique (%)53.7%

Sample

1st row건설자재 야적장 부지조성
2nd row건축물 위 태양광
3rd row종중자연장지 조성
4th row건축물 위 태양광
5th row건축물 위 태양광
ValueCountFrequency (%)
태양광 35
 
7.7%
위 35
 
7.7%
조성 24
 
5.3%
설치(건축물 18
 
4.0%
발전시설 17
 
3.7%
및 15
 
3.3%
부지조성 13
 
2.9%
야적장 12
 
2.6%
건설자재 7
 
1.5%
부지 7
 
1.5%
Other values (153) 271
59.7%
2024-01-10T08:13:50.598044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
318
 
15.7%
설 100
 
4.9%
장 73
 
3.6%
지 67
 
3.3%
물 58
 
2.9%
) 58
 
2.9%
( 58
 
2.9%
양 55
 
2.7%
광 51
 
2.5%
시 51
 
2.5%
Other values (153) 1142
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1590
78.3%
Space Separator 318
 
15.7%
Close Punctuation 59
 
2.9%
Open Punctuation 59
 
2.9%
Decimal Number 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
설 100
 
6.3%
장 73
 
4.6%
지 67
 
4.2%
물 58
 
3.6%
양 55
 
3.5%
광 51
 
3.2%
시 51
 
3.2%
조 50
 
3.1%
건 49
 
3.1%
축 49
 
3.1%
Other values (146) 987
62.1%
Close Punctuation
ValueCountFrequency (%)
) 58
98.3%
] 1
 
1.7%
Open Punctuation
ValueCountFrequency (%)
( 58
98.3%
[ 1
 
1.7%
Decimal Number
ValueCountFrequency (%)
2 4
80.0%
1 1
 
20.0%
Space Separator
ValueCountFrequency (%)
318
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1590
78.3%
Common 441
 
21.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
설 100
 
6.3%
장 73
 
4.6%
지 67
 
4.2%
물 58
 
3.6%
양 55
 
3.5%
광 51
 
3.2%
시 51
 
3.2%
조 50
 
3.1%
건 49
 
3.1%
축 49
 
3.1%
Other values (146) 987
62.1%
Common
ValueCountFrequency (%)
318
72.1%
) 58
 
13.2%
( 58
 
13.2%
2 4
 
0.9%
1 1
 
0.2%
[ 1
 
0.2%
] 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1590
78.3%
ASCII 441
 
21.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
318
72.1%
) 58
 
13.2%
( 58
 
13.2%
2 4
 
0.9%
1 1
 
0.2%
[ 1
 
0.2%
] 1
 
0.2%
Hangul
ValueCountFrequency (%)
설 100
 
6.3%
장 73
 
4.6%
지 67
 
4.2%
물 58
 
3.6%
양 55
 
3.5%
광 51
 
3.2%
시 51
 
3.2%
조 50
 
3.1%
건 49
 
3.1%
축 49
 
3.1%
Other values (146) 987
62.1%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2023-12-06 00:00:00
Maximum2023-12-06 00:00:00
2024-01-10T08:13:50.704741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:13:50.785494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-01-10T08:13:46.679829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:13:46.517093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:13:46.765559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T08:13:46.597037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-01-10T08:13:50.851452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번읍면동리지목지적(제곱미터)용도지역허가내용
연번1.0000.2380.7380.0000.0000.4330.796
읍면동0.2381.0001.0000.7200.4230.7790.914
리0.7381.0001.0000.8790.8230.8690.957
지목0.0000.7200.8791.0000.8150.7420.981
지적(제곱미터)0.0000.4230.8230.8151.0000.0001.000
용도지역0.4330.7790.8690.7420.0001.0000.971
허가내용0.7960.9140.9570.9811.0000.9711.000
2024-01-10T08:13:50.953423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도지역읍면동리지목
용도지역1.0000.3290.3320.252
읍면동0.3291.0000.7720.259
리0.3320.7721.0000.307
지목0.2520.2590.3071.000
2024-01-10T08:13:51.066505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지적(제곱미터)읍면동리지목용도지역
연번1.0000.0320.0660.2200.0000.148
지적(제곱미터)0.0321.0000.2170.3870.4910.000
읍면동0.0660.2171.0000.7720.2590.329
리0.2200.3870.7721.0000.3070.332
지목0.0000.4910.2590.3071.0000.252
용도지역0.1480.0000.3290.3320.2521.000

Missing values

2024-01-10T08:13:46.889609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T08:13:47.044492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-01-10T08:13:47.152356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번시군읍면동리번지지목지적(제곱미터)용도지역허가면적(제곱미터)허가일자허가내용데이터기준일
01보령시내항<NA>376답377자연녹지3772022-10-14건설자재 야적장 부지조성2023-12-06
12보령시대천<NA>1203-6주2180준공업952022-10-14건축물 위 태양광2023-12-06
23보령시주교송학244-2임992보전관리5602022-10-19종중자연장지 조성2023-12-06
34보령시죽정<NA>229장3370계획관리4162022-10-20건축물 위 태양광2023-12-06
45보령시주산야룡452-4 외 1전3534생산관리2022-10-21건축물 위 태양광2023-12-06
56보령시주교송학781-9답1602농림(농업진흥)16022022-10-25어구수선장 부지조성2023-12-06
67보령시남포제석776-5답20627농림(농업진흥)<NA>2022-10-27태양광 발전시설(건축물 위)2023-12-06
78보령시천북학성743-5외4잡+양+전6590계획관리11062022-11-01수산종묘배양장(양어장)2023-12-06
89보령시웅천수부산6-1 외 3임85472보전관리2022-11-01토석채취허가지 내 쇄석시설 설치2023-12-06
910보령시남포삼현82-1 외 1답3025농림(농업진흥)2022-11-01태양광 발전사업(건축물 위)2023-12-06
연번시군읍면동리번지지목지적(제곱미터)용도지역허가면적(제곱미터)허가일자허가내용데이터기준일
126127보령시천북낙동853-4 외1전1091계획관리10912023-11-13농지개량2023-12-06
127128보령시청소죽림산178-1임7270계획관리3702023-11-07물탱크 설치공사2023-12-06
128129보령시웅천평292-12 외 6전+임77242보전관리2839<NA>토석채취허가지 토석 운반로 개설2023-12-06
129130보령시청라나원852-1 외 4전+대4279생산관리9102023-11-20태양광 발전시설 설치(건축물 위)2023-12-06
130131보령시천북장은591답126계획관리1262023-11-20장은2리 마을회관 부지2023-12-06
131132보령시주산창암456-2답2115농림지역(농업진흥)4512023-11-20태양광 발전시설(건축물 위)2023-12-06
132133보령시청소장곡1179-2장3350계획관리2342023-11-21자가용 태양광 발전시설 설치(건축물 위)2023-12-06
133134보령시동대<NA>396-7전1132자연녹지11322023-11-24보령시 동대동 공동주택 신축공사 현장사무실 조성2023-12-06
134135보령시청소죽림837-11 외 2전6096농림지역(농업진흥)46752023-12-01장항선 2단계 개량 노반신설구간 야적장2023-12-06
135136보령시청소진죽1198-3전3899농림지역(농업진흥)13252023-12-01장항선 2단계 개량 노반신설구간 야적장2023-12-06